基于压缩感知平行因子分解的电力系统谐波与间谐波频率估计方法
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南京航空航天大学电子信息工程学院,南京 211106

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国家自然科学基金(61971217,61971218,61631020);江苏省自然科学基金(BK20200444);国家重点研发计划(2020YFB1807602)。


A Harmonic and Inter-harmonic Frequency Estimation Method of Electric Power Systems via Compressed Sensing PARAFAC Method
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College of Electronic and Information Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 211106, China

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    摘要:

    电力系统中的电力电子设备所产生的谐波数量日益增加,谐波问题是一个备受关注的话题。本文通过引入压缩感知理论和平行因子模型,提出了一个用于谐波和间谐波的频率估计算法。先从信息发送终端中获取数据,然后使用欧拉公式将正弦信息转化为空域信息构造多时延输出并建立为平行因子模型,再对模型进行压缩后进行平行因子分析。最后将所得的数据经过贪婪算法重构,再进行频率值的估计。与传统的平行因子计算比较,该计算具有压缩过程,计算工作量相对较小,对数据存储容量需求也较少。所提计算的频谱估计性能与传统的平行因子分解算法(Parallel factorization,PARAFAC)非常接近,而且也比采用旋转不变技术的信号参数估计算法(Estimating signal parameter via rotational invariance techniques,ESPRIT)更加精确。

    Abstract:

    Power quality has always attracted attention. The number of power electronic equipments in the power system and harmonics generated are increasing. The problem of harmonics has always been a topic of concern. This paper proposes a frequency estimation algorithm for power system harmonics and inter-harmonics by introducing the compressed sensing theory and the parallel factor model. First, this paper obtains the data at the signal receiving end, uses Euler’s formula to convert the sine signal into a spatial signal, and constructs the multi-delay output into a parallel factor model. Second, we compress the three slices of the model, and use the trilinear alternating least squares algorithm parallel factorization(PARAFAC). Finally, the obtained data is sparsely reconstructed to obtain the frequency of the automatic pairing. Compared with the traditional parallel factor algorithm, this method has a compression process, a minor calculation, and lower storage capacity requirements. The frequency estimation performance of the proposed algorithm is very similar to that of the traditional PARAFAC method and better than that of the estimating signal parameter via rotational invariance techniques (ESPRIT) method.

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岳衡,张小飞,石莎.基于压缩感知平行因子分解的电力系统谐波与间谐波频率估计方法[J].数据采集与处理,2023,38(1):74-84

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  • 收稿日期:2022-02-25
  • 最后修改日期:2022-11-09
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  • 在线发布日期: 2023-01-25